Review The AI Revolution in Project Management

Every topic or chapter starts with a (fictional) case study, followed by an introduction and the usage of many well-crafted example prompts (ChatGPT) to support you, tips for how to improve these prompts to fit your needs, and elaborates on related ethical considerations and professional responsibility. At the end of each chapter, you get a technical guide with the practical implementation of AI (ChatGPT, Bard, Claude.ai). the last two chapters focusses on AI tools for project management and looking ahead.

Ethical considerations and professional responsibility

The authors use a list of ethical considerations and professional responsibility in AI and highlight these during discussing the different PM related topics: transparency, data privacy, bias mitigation, accountability, environmental considerations, regulatory oversight, human augmentation, hallucinations and data accuracy, and data ownership and training implications.

Stakeholder management

Projects succeed if you as a project leader successfully identify and engage stakeholders, constantly communicating with them and meeting their expectations. AI can help to identify or update stakeholder lists by reviewing email threads or by explaining the project and compare that with similar projects. AI can perform a stakeholder analysis, understanding their interests and needs and generate a power versus interest matrix. AI can analyze stakeholder interactions to determine communication preferences and channels and help to draft personalized memos, progress reports to and answer queries from stakeholders and perform stakeholder sentiment analysis and predict stakeholder behavior.

Building and managing teams

AI reshapes recruiting onboarding, providing a swift, fair, and personalized experience. AI can perform automated screening, communicate with candidates, schedule interviews, and provide feedback, fair hiring due to elimination of bias and automate skill evaluations. AI can tailor onboarding and training initiatives to match your individual employees’ unique needs, skills, and learning styles. AI can augment leadership, facilitating communication, and providing early warning of issues. AI can be used for setting and communicating vision and direction and motivating teams. AI can help in fostering collaboration and can support conflict resolution and decision-making.

Choosing a development approach

AI can help determine the approach to optimize the project management life cycle (predictive, adaptive, and hybrid). AI can help to create a questionnaire to decide which approach. It can provide more helpful insights when specific project management documents and artifacts are uploaded (be aware of confidentiality). You could see AI as the consultant.

Planning for predictive projects

AI can, in an incremental and iterative way, support during project initiation and planning. It can assist with a needs assessment, business case creation and can draft a project charter. It can help in defining the scope, requirements, work breakdown structure and formulate schedules, cost estimation and budgeting. 

Adaptive projects

AI can act as a consultant if you want to run an adaptive (agile) project. It can assist with the articulation of a vision statement, the creation and prioritization of a product backlog. It can identify customer personas. It can break the product backlog into iterations, a release plan, showing the main features. It can give examples of user stories including acceptance criteria, a story map and walking skeleton. AI can build burnup or burndown charts and analyze them.

Monitoring project work performance

AI tools can process vast amounts of data, make predictions, generate reports and converse using natural human language. It can join meetings to take notes, transcribes the conversation, and summarizes key points, action items, and decisions. It can be used for task allocation, resource management, monitoring scope (creep) and schedules including EVA, controlling costs, and maintaining quality.

Risk management

AI can identify and analyze risks as well as plan responses and monitor progress. It can generate (and answer) questionnaires to gather expert opinions. It can construct a risk register. It can perform what-if scenarios in qualitative risk analysis, quantitative risk analysis, predictive modelling using data-driven forecasting, expected monetary value analysis, Monte Carlo analysis and decision tree analysis. AI can plan and develop risk response strategies, monitor risk responses and generate comprehensive risk reports and status summaries.

Finalizing projects

AI can help or act as a consultant during project verification, validation, creating test plans, release (deployment), and closure (building the final project report and presentation, extract key lessons learned).

AI tools

A separate chapter focusses on AI tools for project management. It offers factors needs to be considered when evaluating AI tools. The tools are clustered around several categories: project management systems (task allocation and tracking: Monday.com, Wrike, Asana, OnePlan, PMOtto), scheduling tools (Clockwise), communication and meeting tools (Slack GPT, Microsoft Teams Premium, Zoom AI companion), productivity and documentation tools (Microsoft 265 Copilot, Google Duet), collaboration and brainstorming tools (Miro).

Conclusion

The authors demonstrate in their book “The AI Revolution in Project Management” how generative AI tools, particularly ChatGPT, can significantly aid a project manager. By using the appropriate prompts – and the book provides numerous examples – one can greatly enhance their effectiveness and efficiency in daily tasks. This book is highly recommended for project managers.

To order The AI Revolution in Project Management: Managementboek.nl, bol.